
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch

import numpy as np
import pytest

from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex

from .utils import require_elasticsearch, require_faiss


lowerCamelCase_    :			Optional[int]    =	pytest.mark.integration

@require_faiss
class 							_UpperCamelCase					(       _A	):






			'''simple docstring'''

			def    lowerCAmelCase__						(							self			:							str   ):
							UpperCamelCase_:				int						=    Dataset.from_dict({"""filename""": ["""my_name-train""" + """_""" + str(snake_case_   ) for x in np.arange(30   ).tolist()]}   )
							return dset

			def    lowerCAmelCase__						(							self			:							int   ):
							import faiss

							UpperCamelCase_:				Dataset						=    self._create_dummy_dataset()
							UpperCamelCase_:				Optional[Any]						=    dset.map(
							    lambda snake_case_    ,						snake_case_   : {"vecs": i * np.ones(5    ,						dtype=np.floataa   )}    ,						with_indices=snake_case_    ,						keep_in_memory=snake_case_   )
							UpperCamelCase_:				Union[str, Any]						=    dset.add_faiss_index("""vecs"""    ,						batch_size=100    ,						metric_type=faiss.METRIC_INNER_PRODUCT   )
							UpperCamelCase_, UpperCamelCase_:				Any						=    dset.get_nearest_examples("""vecs"""    ,						np.ones(5    ,						dtype=np.floataa   )   )
							self.assertEqual(examples["""filename"""][0]    ,						"""my_name-train_29"""   )
							dset.drop_index("""vecs"""   )

			def    lowerCAmelCase__						(							self			:							Any   ):
							import faiss

							UpperCamelCase_:				Dataset						=    self._create_dummy_dataset()
							dset.add_faiss_index_from_external_arrays(
							    external_arrays=np.ones((30, 5)   ) * np.arange(30   ).reshape(-1    ,						1   )    ,						index_name="""vecs"""    ,						batch_size=100    ,						metric_type=faiss.METRIC_INNER_PRODUCT    ,						)
							UpperCamelCase_, UpperCamelCase_:				Tuple						=    dset.get_nearest_examples("""vecs"""    ,						np.ones(5    ,						dtype=np.floataa   )   )
							self.assertEqual(examples["""filename"""][0]    ,						"""my_name-train_29"""   )

			def    lowerCAmelCase__						(							self			:							List[str]   ):
							import faiss

							UpperCamelCase_:				Dataset						=    self._create_dummy_dataset()
							dset.add_faiss_index_from_external_arrays(
							    external_arrays=np.ones((30, 5)   ) * np.arange(30   ).reshape(-1    ,						1   )    ,						index_name="""vecs"""    ,						metric_type=faiss.METRIC_INNER_PRODUCT    ,						)

							# Setting delete=False and unlinking manually is not pretty... but it is required on Windows to
							# ensure somewhat stable behaviour. If we don't, we get PermissionErrors. This is an age-old issue.
							# see https://bugs.python.org/issue14243 and
							# https://stackoverflow.com/questions/23212435/permission-denied-to-write-to-my-temporary-file/23212515
							with tempfile.NamedTemporaryFile(delete=snake_case_   ) as tmp_file:
											dset.save_faiss_index("""vecs"""    ,						tmp_file.name   )
											dset.load_faiss_index("""vecs2"""    ,						tmp_file.name   )
							os.unlink(tmp_file.name   )

							UpperCamelCase_, UpperCamelCase_:				Tuple						=    dset.get_nearest_examples("""vecs2"""    ,						np.ones(5    ,						dtype=np.floataa   )   )
							self.assertEqual(examples["""filename"""][0]    ,						"""my_name-train_29"""   )

			def    lowerCAmelCase__						(							self			:							List[str]   ):
							UpperCamelCase_:				Dataset						=    self._create_dummy_dataset()
							dset.add_faiss_index_from_external_arrays(
							    external_arrays=np.ones((30, 5)   ) * np.arange(30   ).reshape(-1    ,						1   )    ,						index_name="""vecs"""   )
							dset.drop_index("""vecs"""   )
							self.assertRaises(snake_case_    ,						partial(dset.get_nearest_examples    ,						"""vecs2"""    ,						np.ones(5    ,						dtype=np.floataa   )   )   )




			def    lowerCAmelCase__						(							self			:							Optional[int]   ):
							from elasticsearch import Elasticsearch

							UpperCamelCase_:				Dataset						=    self._create_dummy_dataset()
							with patch("""elasticsearch.Elasticsearch.search"""   ) as mocked_search, patch(
							    """elasticsearch.client.IndicesClient.create"""   ) as mocked_index_create, patch("""elasticsearch.helpers.streaming_bulk"""   ) as mocked_bulk:
											UpperCamelCase_:				Union[str, Any]						=    {"""acknowledged""": True}
											mocked_bulk.return_value([(True, None)] * 30   )
											UpperCamelCase_:				str						=    {"""hits""": {"""hits""": [{"""_score""": 1, """_id""": 29}]}}
											UpperCamelCase_:				Optional[Any]						=    Elasticsearch()

											dset.add_elasticsearch_index("""filename"""    ,						es_client=snake_case_   )
											UpperCamelCase_, UpperCamelCase_:				List[str]						=    dset.get_nearest_examples("""filename"""    ,						"""my_name-train_29"""   )
											self.assertEqual(examples["""filename"""][0]    ,						"""my_name-train_29"""   )




@require_faiss
class 							_UpperCamelCase					(       _A	):






			'''simple docstring'''

			def    lowerCAmelCase__						(							self			:							List[str]   ):
							import faiss

							UpperCamelCase_:				List[str]						=    FaissIndex(metric_type=faiss.METRIC_INNER_PRODUCT   )

							# add vectors
							index.add_vectors(np.eye(5    ,						dtype=np.floataa   )   )
							self.assertIsNotNone(index.faiss_index   )
							self.assertEqual(index.faiss_index.ntotal    ,						5   )
							index.add_vectors(np.zeros((5, 5)    ,						dtype=np.floataa   )   )
							self.assertEqual(index.faiss_index.ntotal    ,						10   )

							# single query
							UpperCamelCase_:				Optional[Any]						=    np.zeros(5    ,						dtype=np.floataa   )
							UpperCamelCase_:				Tuple						=    1
							UpperCamelCase_, UpperCamelCase_:				Optional[int]						=    index.search(snake_case_   )
							self.assertRaises(snake_case_    ,						index.search    ,						query.reshape(-1    ,						1   )   )
							self.assertGreater(scores[0]    ,						0   )
							self.assertEqual(indices[0]    ,						1   )

							# batched queries
							UpperCamelCase_:				str						=    np.eye(5    ,						dtype=np.floataa   )[::-1]
							UpperCamelCase_, UpperCamelCase_:				Optional[int]						=    index.search_batch(snake_case_   )
							self.assertRaises(snake_case_    ,						index.search_batch    ,						queries[0]   )
							UpperCamelCase_:				Union[str, Any]						=    [scores[0] for scores in total_scores]
							UpperCamelCase_:				Optional[Any]						=    [indices[0] for indices in total_indices]
							self.assertGreater(np.min(snake_case_   )    ,						0   )
							self.assertListEqual([4, 3, 2, 1, 0]    ,						snake_case_   )

			def    lowerCAmelCase__						(							self			:							Union[str, Any]   ):
							import faiss

							UpperCamelCase_:				Union[str, Any]						=    FaissIndex(string_factory="""Flat"""   )
							index.add_vectors(np.eye(5    ,						dtype=np.floataa   )   )
							self.assertIsInstance(index.faiss_index    ,						faiss.IndexFlat   )
							UpperCamelCase_:				Any						=    FaissIndex(string_factory="""LSH"""   )
							index.add_vectors(np.eye(5    ,						dtype=np.floataa   )   )
							self.assertIsInstance(index.faiss_index    ,						faiss.IndexLSH   )
							with self.assertRaises(snake_case_   ):
											UpperCamelCase_:				int						=    FaissIndex(string_factory="""Flat"""    ,						custom_index=faiss.IndexFlat(5   )   )

			def    lowerCAmelCase__						(							self			:							Optional[int]   ):
							import faiss

							UpperCamelCase_:				Optional[int]						=    faiss.IndexFlat(5   )
							UpperCamelCase_:				Dict						=    FaissIndex(custom_index=snake_case_   )
							index.add_vectors(np.eye(5    ,						dtype=np.floataa   )   )
							self.assertIsInstance(index.faiss_index    ,						faiss.IndexFlat   )




			def    lowerCAmelCase__						(							self			:							int   ):
							import faiss

							UpperCamelCase_:				Optional[Any]						=    FaissIndex(metric_type=faiss.METRIC_INNER_PRODUCT   )
							index.add_vectors(np.eye(5    ,						dtype=np.floataa   )   )

							# Setting delete=False and unlinking manually is not pretty... but it is required on Windows to
							# ensure somewhat stable behaviour. If we don't, we get PermissionErrors. This is an age-old issue.
							# see https://bugs.python.org/issue14243 and
							# https://stackoverflow.com/questions/23212435/permission-denied-to-write-to-my-temporary-file/23212515
							with tempfile.NamedTemporaryFile(delete=snake_case_   ) as tmp_file:
											index.save(tmp_file.name   )
											UpperCamelCase_:				Optional[Any]						=    FaissIndex.load(tmp_file.name   )
							os.unlink(tmp_file.name   )

							UpperCamelCase_:				List[Any]						=    np.zeros(5    ,						dtype=np.floataa   )
							UpperCamelCase_:				Optional[int]						=    1
							UpperCamelCase_, UpperCamelCase_:				str						=    index.search(snake_case_   )
							self.assertGreater(scores[0]    ,						0   )
							self.assertEqual(indices[0]    ,						1   )







@require_faiss
def 							A__       (    lowerCamelCase    )	->						Optional[int]:
				import faiss

				UpperCamelCase_:				Tuple						=    FaissIndex(metric_type=faiss.METRIC_INNER_PRODUCT    )
				index.add_vectors(np.eye(5  ,     dtype=np.floataa    )    )

				UpperCamelCase_:				Optional[int]						=    """index.faiss"""
				UpperCamelCase_:				Any						=    F'''mock://{index_name}'''
				index.save(lowerCamelCase  ,     storage_options=mockfs.storage_options    )
				UpperCamelCase_:				Any						=    FaissIndex.load(lowerCamelCase  ,     storage_options=mockfs.storage_options    )

				UpperCamelCase_:				Optional[int]						=    np.zeros(5  ,     dtype=np.floataa    )
				UpperCamelCase_:				List[str]						=    1
				UpperCamelCase_, UpperCamelCase_:				Tuple						=    index.search(lowerCamelCase    )
				assert scores[0] > 0
				assert indices[0] == 1





@require_elasticsearch
class 							_UpperCamelCase					(       _A	):






			'''simple docstring'''

			def    lowerCAmelCase__						(							self			:							int   ):
							from elasticsearch import Elasticsearch

							with patch("""elasticsearch.Elasticsearch.search"""   ) as mocked_search, patch(
							    """elasticsearch.client.IndicesClient.create"""   ) as mocked_index_create, patch("""elasticsearch.helpers.streaming_bulk"""   ) as mocked_bulk:
											UpperCamelCase_:				Optional[Any]						=    Elasticsearch()
											UpperCamelCase_:				Any						=    {"""acknowledged""": True}
											UpperCamelCase_:				Union[str, Any]						=    ElasticSearchIndex(es_client=snake_case_   )
											mocked_bulk.return_value([(True, None)] * 3   )
											index.add_documents(["""foo""", """bar""", """foobar"""]   )

											# single query
											UpperCamelCase_:				List[Any]						=    """foo"""
											UpperCamelCase_:				Optional[Any]						=    {"""hits""": {"""hits""": [{"""_score""": 1, """_id""": 0}]}}
											UpperCamelCase_, UpperCamelCase_:				Union[str, Any]						=    index.search(snake_case_   )
											self.assertEqual(scores[0]    ,						1   )
											self.assertEqual(indices[0]    ,						0   )

											# single query with timeout
											UpperCamelCase_:				List[Any]						=    """foo"""
											UpperCamelCase_:				Optional[Any]						=    {"""hits""": {"""hits""": [{"""_score""": 1, """_id""": 0}]}}
											UpperCamelCase_, UpperCamelCase_:				Tuple						=    index.search(snake_case_    ,						request_timeout=30   )
											self.assertEqual(scores[0]    ,						1   )
											self.assertEqual(indices[0]    ,						0   )

											# batched queries
											UpperCamelCase_:				int						=    ["""foo""", """bar""", """foobar"""]
											UpperCamelCase_:				Any						=    {"""hits""": {"""hits""": [{"""_score""": 1, """_id""": 1}]}}
											UpperCamelCase_, UpperCamelCase_:				Union[str, Any]						=    index.search_batch(snake_case_   )
											UpperCamelCase_:				Any						=    [scores[0] for scores in total_scores]
											UpperCamelCase_:				Dict						=    [indices[0] for indices in total_indices]
											self.assertGreater(np.min(snake_case_   )    ,						0   )
											self.assertListEqual([1, 1, 1]    ,						snake_case_   )

											# batched queries with timeout
											UpperCamelCase_:				str						=    ["""foo""", """bar""", """foobar"""]
											UpperCamelCase_:				Any						=    {"""hits""": {"""hits""": [{"""_score""": 1, """_id""": 1}]}}
											UpperCamelCase_, UpperCamelCase_:				str						=    index.search_batch(snake_case_    ,						request_timeout=30   )
											UpperCamelCase_:				str						=    [scores[0] for scores in total_scores]
											UpperCamelCase_:				Union[str, Any]						=    [indices[0] for indices in total_indices]
											self.assertGreater(np.min(snake_case_   )    ,						0   )
											self.assertListEqual([1, 1, 1]    ,						snake_case_   )








from __future__ import annotations







def 							A__       (    lowerCamelCase    )	->						int:
				UpperCamelCase_:				Optional[Any]						=    len(lowerCamelCase    ) // 2

				# choose the middle 3 elements
				UpperCamelCase_:				Tuple						=    lst[m - 1 : m + 2]

				# if middle element is peak
				if three[1] > three[0] and three[1] > three[2]:
								return three[1]

				# if increasing, recurse on right
				elif three[0] < three[2]:
								if len(lst[:m]    ) == 2:
												m -= 1
								return peak(lst[m:]    )

				# decreasing
				else:
								if len(lst[:m]    ) == 2:
												m += 1
								return peak(lst[:m]    )


if __name__ == "__main__":
							import doctest

							doctest.testmod()






